Facial expression recognition and interaction method based on GPU acceleration

Abstract

The invention relates to a facial expression recognition and interaction method based on GPU acceleration, and belongs to the field of mode recognition. The method establishes a method framework of rapidly recognizing micro-expression based on GPU acceleration. The method comprises: firstly, acquiring user facial images through an ordinary camera or a video, performing facial detection and facial feature point recognition by using a recognition method based on Haar characteristics and AdaBoost, to recognize position coordinates of user pupils, apex nasi, etc., dividing a face into a plurality of critical areas, using a Gabor filtering method based on GPU acceleration, performing Gabor filtering on the whole face in five dimensions and eight directions, and performing feature extraction on the critical areas near the facial feature points. According to the method, features of CK, CK+, MMI extracted from a database are marked in labels according to whether micro-expression occurs or not, and through putting the features with the labels to a SVM, a recognition model is obtained. A user puts the extracted features into the recognition model to obtain specific information of the micro-expression.

Description

technical field [0001] The invention relates to the technical fields of computer digital multimedia, augmented reality and somatosensory interaction, in particular to a method for detecting and interacting with facial expressions based on a common camera, in particular to a method for identifying and interacting with facial expressions based on GPU acceleration. Background technique [0002] The human face is one of the most expressive channels in non-verbal communication, and facial expressions provide clues for studying emotions, intentions, and personality. The ability to accurately and efficiently recognize facial expressions can provide support for many applications, and there is huge room for imagination. [0003] Over the past few decades, many computer systems have been built to understand or interact with human expressions. Most systems recognize expressions as some archetypal expressions (happy, surprised, angry, sad, fearful, disgusted). In everyday life, th...

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to provide a face expression recognition and interaction method based on GPU acceleration, which solves the problems of low face recognition efficiency in the prior art

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